These files are GGML format model files for CalderaAI's 30B Epsilon.

GGML files are for CPU + GPU inference using llama.cpp and libraries and UIs which support this format, such as:

Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction: {prompt}

### Response:

These are guaranteed to be compatible with any UIs, tools and libraries released since late May. They may be phased out soon, as they are largely superseded by the new k-quant methods.

These new quantisation methods are compatible with llama.cpp as of June 6th, commit 2d43387.

They are now also compatible with recent releases of text-generation-webui, KoboldCpp, llama-cpp-python, ctransformers, rustformers and most others. For compatibility with other tools and libraries, please check their documentation.

Note: the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.

I use the following command line; adjust for your tastes and needs:

Change -t 10 to the number of physical CPU cores you have. For example if your system has 8 cores/16 threads, use -t 8.

Change -ngl 32 to the number of layers to offload to GPU. Remove it if you don't have GPU acceleration.

If you want to have a chat-style conversation, replace the -p <PROMPT> argument with -i -ins

Further instructions here: text-generation-webui/docs/llama.cpp-models.md.

For further support, and discussions on these models and AI in general, join us at:

Thanks to the chirper.ai team!

I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training.

If you're able and willing to contribute it will be most gratefully received and will help me to keep providing more models, and to start work on new AI projects.

Donaters will get priority support on any and all AI/LLM/model questions and requests, access to a private Discord room, plus other benefits.

Special thanks to: Luke from CarbonQuill, Aemon Algiz.

Patreon special mentions: Slarti, Chadd, John Detwiler, Pieter, zynix, K, Mano Prime, ReadyPlayerEmma, Ai Maven, Leonard Tan, Edmond Seymore, Joseph William Delisle, Luke @flexchar, Fred von Graf, Viktor Bowallius, Rishabh Srivastava, Nikolai Manek, Matthew Berman, Johann-Peter Hartmann, ya boyyy, Greatston Gnanesh, Femi Adebogun, Talal Aujan, Jonathan Leane, terasurfer, David Flickinger, William Sang, Ajan Kanaga, Vadim, Artur Olbinski, Raven Klaugh, Michael Levine, Oscar Rangel, Randy H, Cory Kujawski, RoA, Dave, Alex, Alexandros Triantafyllidis, Fen Risland, Eugene Pentland, vamX, Elle, Nathan LeClaire, Khalefa Al-Ahmad, Rainer Wilmers, subjectnull, Junyu Yang, Daniel P. Andersen, SuperWojo, LangChain4j, Mandus, Kalila, Illia Dulskyi, Trenton Dambrowitz, Asp the Wyvern, Derek Yates, Jeffrey Morgan, Deep Realms, Imad Khwaja, Pyrater, Preetika Verma, biorpg, Gabriel Tamborski, Stephen Murray, Spiking Neurons AB, Iucharbius, Chris Smitley, Willem Michiel, Luke Pendergrass, Sebastain Graf, senxiiz, Will Dee, Space Cruiser, Karl Bernard, Clay Pascal, Lone Striker, transmissions 11, webtim, WelcomeToTheClub, Sam, theTransient, Pierre Kircher, chris gileta, John Villwock, Sean Connelly, Willian Hasse

Thank you to all my generous patrons and donaters!

Epsilon is an instruct based general purpose model assembled from hand picked models and LoRAs. There is no censorship and it follows instructions in the Alpaca format. This means you can create your own rules in the context memory of your inference system of choice [mainly KoboldAI or Text Generation Webui and chat UIs like SillyTavern and so on].

This model is the result of an experimental use of LoRAs on language models and model merges. [] = applied as LoRA to a composite model | () = combined as composite models 30B-Epsilon = [SuperCOT[SuperHOT-prototype13b-8192[(wizardlmuncensored+((hippogriff+manticore)+(StoryV2))]

Alpaca's instruct format can be used to do many things, including control of the terms of behavior between a user and a response from an agent in chat. Below is an example of a command injected into memory.

### Instruction:
Make Narrator function as a text based adventure game that responds with verbose, detailed, and creative descriptions of what happens next after Player's response.
Make Player function as the player input for Narrator's text based adventure game, controlling a character named (insert character name here, their short bio, and
whatever quest or other information to keep consistent in the interaction).

### Response:
{an empty new line here}

All datasets from all models and LoRAs used were documented and reviewed as model candidates for merging. Model candidates were based on five core principles: creativity, logic, inference, instruction following, and longevity of trained responses. SuperHOT-prototype30b-8192 was used in this mix, not the 8K version; the prototype LoRA seems to have been removed [from HF] as of this writing. The GPT4Alpaca LoRA from Chansung was removed from this amalgam following a thorough review of where censorship and railroading the user came from in 33B-Lazarus. This is not a reflection of ChanSung's excellent work - it merely did not fit the purpose of this model.

manticore-30b-chat-pyg-alpha [Epoch0.4] by openaccess-ai-collective

hippogriff-30b-chat by openaccess-ai-collective

WizardLM-33B-V1.0-Uncensored by ehartford

Storytelling-LLaMa-LoRA [30B, Version 2] by GamerUnTouch

SuperCOT-LoRA [30B] by kaiokendev

SuperHOT-LoRA-prototype30b-8192 [30b, not 8K version, but a removed prototype] by kaiokendev

https://huggingface.co/kaiokendev/superhot-30b-8k-no-rlhf-test [Similar LoRA to one since removed that was used in making this model.]

Also thanks to Meta for LLaMA and to each and every one of you who developed these fine-tunes and LoRAs.